GenAI in drug discovery for underrepresented populations: ethical and epistemological implications

Background

Generative AI (GenAI) is expected to transform the field of drug discovery by accelerating the process, reducing costs, and uncovering new therapeutic possibilities. For example, AI tools can analyse vast amounts of biological and chemical datasets to identify disease-associated targets, and help design novel molecular structures to enhance drug efficacy, minimise toxicity and improve pharmacokinetics.

However, the quality of AI outputs is directly related to the quality of the data upon which they are developed and trained. This raises questions regarding the epistemological and ethical justification of relying on GenAI tools in drug discovery for populations that have been systematically excluded from research, and on which very few data exist. Using paediatrics as a case study, this project will investigate what would constitute an appropriate use of GenAI tools in drug discovery for underrepresented populations in clinical research. 

research experience, research methods and skills training

Research experience in using practical ethics methods, skills in developing ethical frameworks in research ethics. Training in academic writing and presentations.

PROSPECTIVE STUDENT

The idea candidate will have an undergraduate degree in philosophy and Master’s degree in philosophy of science, epistemology and/or ethics.